Principal Computational Statistician

Role Summary

Principal Computational Statistician role at Lilly. Responsible for statistical analysis, collaboration with study personnel, data quality planning, and communicating results for regulatory submissions and publications. Focus on applying SAS/R programming, statistical methodology, and ongoing professional development within a regulated environment.

Responsibilities

• Collaborate with statistical colleagues and study personnel to provide input to statistical analysis plans, write reports and communicate results, and assist/respond to regulatory queries.
• Assist in selecting statistical methods for data analysis, author the corresponding sections of the analysis plan, and conduct the actual analysis once a reporting database is created.
• Collaborate with data management in planning and implementing data quality assurance plans.
• Maintain proficiency with SAS/R programming and statistical methodology and apply new methods as appropriate.
• Justify methods selected and implement previously outlined analysis plans.
• Conduct peer-review of work products from statistical colleagues.
• Use current technologies and tools for conducting clinical trial analysis.
• Assist in communicating study results via regulatory submissions and manuscripts, and communicate with key customers.
• Understand relevant disease states to enhance customer focus and collaboration; stay informed of technological advances.
• Perform work in compliance with applicable policies, procedures, processes, and training.

Qualifications

• Master’s degree in Statistics, Biostatistics or MSPH with concentration in Statistics or Biostatistics, or relevant areas of science
• 3+ years of statistical analysis/programming experience
• Proficiency in statistical programming languages/software such as SAS, R, Spotfire, etc.

Skills

• Interpersonal/teamwork skills for effective interactions
• Technical growth and application with solid understanding of statistics and statistical software
• Self-management with focus on timely, accurate deliverables
• Creativity and innovation; problem solving and attention to detail
• Data analysis, technology, and systems expertise